Publications by authors named "Sinan Shi"

Understanding genetic differences between populations is essential for avoiding confounding in genome-wide association studies and improving polygenic score (PGS) portability. We developed a statistical pipeline to infer fine-scale Ancestry Components and applied it to UK Biobank data. Ancestry Components identify population structure not captured by widely used principal components, improving stratification correction for geographically correlated traits.

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We built a reference panel with 342 million autosomal variants using 78,195 individuals from the Genomics England (GEL) dataset, achieving a phasing switch error rate of 0.18% for European samples and imputation quality of r = 0.75 for variants with minor allele frequencies as low as 2 × 10 in white British samples.

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Objectives: To describe the epidemiology of sepsis in critical care by applying the Sepsis-3 criteria to electronic health records.

Design: Retrospective cohort study using electronic health records.

Setting: Ten ICUs from four U.

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Inexpensive genotyping methods are essential to modern genomics. Here we present QUILT, which performs diploid genotype imputation using low-coverage whole-genome sequence data. QUILT employs Gibbs sampling to partition reads into maternal and paternal sets, facilitating rapid haploid imputation using large reference panels.

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Knowledge of genome-wide genealogies for thousands of individuals would simplify most evolutionary analyses for humans and other species, but has remained computationally infeasible. We have developed a method, Relate, scaling to >10,000 sequences while simultaneously estimating branch lengths, mutational ages and variable historical population sizes, as well as allowing for data errors. Application to 1,000 Genomes Project haplotypes produces joint genealogical histories for 26 human populations.

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The genetic architecture of brain structure and function is largely unknown. To investigate this, we carried out genome-wide association studies of 3,144 functional and structural brain imaging phenotypes from UK Biobank (discovery dataset 8,428 subjects). Here we show that many of these phenotypes are heritable.

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Objective: To build and curate a linkable multi-centre database of high resolution longitudinal electronic health records (EHR) from adult Intensive Care Units (ICU). To develop a set of open-source tools to make these data 'research ready' while protecting patient's privacy with a particular focus on anonymisation.

Materials And Methods: We developed a scalable EHR processing pipeline for extracting, linking, normalising and curating and anonymising EHR data.

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